FRED T10YIE — Daily CSV Download (10-Year Breakeven Inflation)
The 10-year breakeven inflation rate measures the market’s expectation of average annual CPI inflation over the next decade — a critical input for assessing whether inflation expectations remain “anchored” around the Fed’s 2% target. Daily observations from FRED series T10YIE.
Dataset: US 10-Year Breakeven Inflation Rate (2003–2026) · Updated —
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Source: FRED series T10YIE · Federal Reserve Bank of St. Louis
Macro Takeaway
This indicator is a key component of the macro-financial monitoring framework. Its current level relative to its historical distribution — captured in the percentile and z-score above — provides immediate context for whether conditions are historically normal, stretched, or compressed.
Cross-referencing with the 10-year Treasury yield and the yield curve spread helps situate this indicator within the broader macro regime.
Dataset Overview
| Indicator | US 10-Year Breakeven Inflation Rate (2003–2026) |
|---|---|
| Geography | United States |
| Frequency | Daily (business days) |
| Period | 2003–2026 |
| Variables | date, breakeven_10y |
| Format | CSV, Excel (XLSX) |
| Sources | Federal Reserve Bank of St. Louis — FRED |
| Last updated | — |
Dataset Variables
The CSV and Excel files contain the following columns.
| Column | Type | Description |
|---|---|---|
date | Date (YYYY-MM-DD) | Observation date |
breakeven_10y | Float | breakeven_10y value |
Column names match the CSV headers exactly.
Download the Complete Dataset
The full dataset is available in CSV and Excel formats.
FRED Direct CSV Access
The underlying data is available from FRED under series code T10YIE:
https://fred.stlouisfed.org/graph/fredgraph.csv?id=T10YIE
Direct CSV Access — Eco3min Structured Dataset
https://eco3min.fr/dataset/us-inflation-expectations-10y.csv
This URL returns the complete dataset in CSV format. It can be used directly in pandas, R, curl, or any data tool.
Using the Dataset in Python
import pandas as pd url = "https://eco3min.fr/dataset/us-inflation-expectations-10y.csv" df = pd.read_csv(url, parse_dates=["date"]) print(df.head()) print(df["t10yie"].describe())
Using the Dataset in R
library(readr) url <- "https://eco3min.fr/dataset/us-inflation-expectations-10y.csv" df <- read_csv(url) head(df) summary(df$t10yie)
Both examples load the dataset directly from the URL — no download or API key required.
Methodology
The primary data source is the Federal Reserve’s FRED database, series T10YIE. The data is published by the relevant US government agency and made available through FRED with consistent formatting and metadata.
This dataset is updated weekly (Saturday 08:00 UTC) via automated pull from the FRED API.
Historical Regimes
Historical regime analysis for this dataset will be added in a future update. The key stats block above provides immediate context for the current reading relative to the full historical distribution.
Related Macroeconomic Datasets
The 10-year breakeven is derived from the spread between nominal Treasuries and TIPS. It reflects the bond market’s collective inflation forecast — a critical input for the Fed’s assessment of whether long-term expectations remain “anchored.” Cross-reference with realized inflation (CPI, PCE) to measure how well the market’s forecast matches reality.
- 5-Year Breakeven Inflation — Medium-term expectations; more volatile, faster to react
- US CPI Inflation History — Realized inflation against which breakevens can be assessed
- PCE Inflation — The Fed’s official 2% target measure
- US 10-Year Treasury Yield — The nominal rate that combines real rate + breakeven
- Real 10-Year Treasury Yield — The other half of the nominal yield decomposition
Related Research
Breakeven inflation rates are a key input to the real interest rate calculation and to equity valuation frameworks. When breakevens spike, real rates compress — shifting the rate-valuation regime. The studies below connect inflation expectations to the broader analytical framework.
Sources
- Federal Reserve Bank of St. Louis — FRED database